Uncountable

What Uncountable does

Uncountable is an AI Platform designed for end-to-end product development, serving product organizations across various industries including chemicals, advanced materials, consumer goods, food and agriculture, and pharmaceuticals. The platform captures, structures, and connects data across the full product lifecycle, from ideation to commercialization. It aims to unify fragmented data from legacy point systems into a single data layer, powering AI-driven innovation, productivity, and risk reduction. Uncountable provides solutions for R&D, Quality Control (QC), and Product Lifecycle Management (PLM) data, offering tools like Electronic Lab Notebooks (ELN), Laboratory Information Management Systems (LIMS), and Quality Management Systems (QMS). The platform leverages proprietary machine learning algorithms tailored for scientific experimentation to optimize performance and accelerate product development.

Products

• Uncountable AI PlatformAn AI platform for end-to-end product development, integrating R&D, QC, and PLM data. It captures, structures, and connects data across the full product lifecycle, from ideation to commercialization, to power AI-driven innovation, productivity, and risk reduction.
• Bodie AI AssistantAn AI assistant integrated into the Uncountable platform that makes search, analysis, and reporting easier and more automated. It can find experiments, summarize projects, generate visualizations, write notebooks, and perform direct platform actions.
• DOE CopilotA feature that helps set up and understand designed experiments using project-specific data.
• Integrated Electronic Lab Notebook (ELN)A solution for capturing, structuring, and managing laboratory data, offering features like customizable parameters, searchable repositories, real-time reporting, audit-ready versioning, and regulatory compliance support.
• Integrated LIMS for Enterprise R&DA Laboratory Information Management System designed to unify vital laboratory information, streamline scientific data and workflows, manage data across organizations, automate sample and inventory tracking, and contextualize complex datasets.
• Integrated QC LIMS for EnterprisesA Quality Control LIMS solution that centralizes quality data and documentation, manages quality events, automates workflows, ensures traceability and audit-readiness, and integrates with R&D and production systems.
• Cloud PLMA cloud-based Product Lifecycle Management solution that centralizes formulations, bills of materials, test data, process parameters, and documentation in a single searchable platform, offering full-lifecycle visibility and cross-functional alignment.
• QMSA Quality Management System that helps manage quality events, control plans, test results, and documentation in a single platform, ensuring compliance and traceability.

Key capabilities

• AI-driven innovation, productivity, and risk reduction
• Unified data layer across the full product lifecycle
• Conversational AI assistant (Bodie) for search, analysis, and reporting
• Automated insight generation and report creation
• Plain language chart creation and visualizations
• Direct platform actions (edit tables, create records, update fields)
• DOE Copilot for designed experiments
• Searchable experiment repository
• Automated inventory management and regulatory compliance
• Formulation and experimentation tools
• Scientific Data Management System (SDMS)
• Advanced visualizations & reporting
• Predictive formulation modeling
• Production pattern recognition
• AI-guided optimization
• Formulation-first data model
• Full-lifecycle visibility and traceability
• Cross-functional alignment
• Company-wide visibility of laboratory information
• Predictive calculations & experiment suggestions
• Inventory and workflow task management
• Integration with critical regulatory & pricing information
• Collaborative platform for efficient teamwork
• Centralized data capture in a secure location
• Proprietary machine learning algorithms for scientific experimentation
• Advanced security features (SOC 2, ISO 27001, FDA 21 CFR 11, GMP compliance)
• Audit trail of all actions
• Electronic signature support
• Full lot traceability
• Shelf life management
• Integration with Microsoft Office
• Configurable workflow templates
• Consistent data capture with enforced fields
• Process visibility and bottleneck identification
• Audit-ready versioning and change history tracking
• Configurable and adaptable LIMS solution
• Instrument & equipment integrations (400+ types)
• Automated workflows and task scheduling
• Customizable permissions and accessibility
• Seamless data management and integration
• Scalability and flexibility
• Stability testing & tracking module
• Built-in project management
• Centralized global research
• 20+ visualization tools (scatter, box, radar, violin, curve, correlation grid, image compare)
• Statistical analysis tools (ANOVA, DOE creation)
• Built-in notebook for report creation
• Export reports to PDF, Word, PowerPoint
• Real-time data updates in graphs
• Automated data ingestion
• High throughput screening
• Predictive tools for new experiments or critical variables
• Multi-step process workflows
• Lab requests assignment and tracking
• Sample tracking across multiple labs
• Unit control for formulations (parts per hundred, percentages)
• Data aggregation from different scientists, labs, production lines, locations
• One-click correlation analysis
• Live SPC charting for QC/QA
• Automated sampling and testing workflows
• Real-time dashboards for quality
• Unified hub for quality management
• Structured, searchable quality records
• AI tooling for quicker root cause analysis in QC
• Link quality to product data
• Workflow automation for test reviews, CAPA, non-conformance management
• Task & notification management for quality
• Built-in QMS & PLM integration for quality events
• Instrument & ERP integration for quality data

Use cases

• End-to-end product development
• R&D data management
• Quality control (QC) data management
• Product lifecycle management (PLM)
• Experiment search and discovery
• Automated report generation
• Knowledge summarization and technical question answering
• Data visualization and charting
• Editing tables and updating fields directly in platform
• Setting up and understanding designed experiments (DOE)
• Centralizing formulation, process, and quality data
• Faster iteration and reduced scale-up surprises in F&B R&D
• Accelerating nutrition label creation
• Benchmarking R&D data maturity
• Planning lab software implementation
• Choosing a Laboratory Information Management System (LIMS)
• Choosing an Electronic Lab Notebook (ELN)
• Lab inventory tracking and management
• Transforming QC/QA in manufacturing
• Creating data infrastructure for AI-driven formulation & measurement
• Managing laboratory information in a single, shareable workbook
• Collaborating efficiently across locations and functions
• Capturing and centralizing formulation and experiment data
• Testing and innovating faster with visualization tools
• Optimizing performance using advanced AI
• Leveraging cross-project learnings
• Predicting new formulation performance
• Receiving optimized experiment suggestions
• Upholding compliance and regulatory standards (SOC 2, ISO 27001, FDA 21 CFR 11, GMP)
• Designing large scale multivariate experiments
• High throughput screening for promising candidates
• Using past data to suggest new experiments or identify critical variables
• Creating complex multi-step workflows
• Requesting, assigning, and tracking lab work
• Monitoring sample locations and results
• Tracking inputs across experiments by lot number
• Automated data ingestion
• Consolidating data in paint and coatings R&D
• Identifying high performance conditions in multi-parametric formulations
• Recording flexible output types (numbers, curves, images, colors)
• Calculating cost, solids %, and other quantities in real-time
• Comparing and visualizing outputs from various resources in cosmetics/consumer goods
• Aggregating and comparing synthesis pathway data for cost reduction and supply chain resilience
• Utilizing machine learning models for scientific breakthroughs
• Linking to regulatory databases for ingredient usage
• Formulating in various units for plastics & compounding
• Comparing data from different scientists, labs, production lines, locations
• Accelerating discovery of new screening experiments for polymers
• Analyzing trends/trade-offs with one-click correlation analysis
• Recording flexible experiment flows
• Streamlining R&D data management processes
• Centralizing experimental data across global teams
• Accelerating innovation in battery materials
• Improving research efficiency and reducing redundant testing in plant-based products
• Boosting R&D traceability and lab management
• Improving data management and project efficiency for adhesives and sealants
• Accelerating research and development in chemicals
• Revolutionizing product development for optical fiber coatings
• Streamlining data management and automating workflows
• Increasing product development in abrasives
• Accelerating development of high-performance batteries
• Streamlining global collaboration in R&D
• Optimizing experimental processes in alternative meat industry
• Tracing failures to root cause and designing better materials in advanced materials R&D
• Managing dense, regulated data in drug development (small molecule, biologics, cell & gene therapy)
• Structuring discovery, formulation, and process data in pharma & biotech
• Screening assays for cancer enzyme suppression
• Aggregating synthesis pathway data for cost & efficiency in small molecule R&D
• Running correlation analysis on tablet formulations
• Using ML to suggest optimal formulations in small molecule R&D
• Identifying high performing cell cultures in biologics
• Tracking cell line development cycles
• Projecting optimal media components with ML in biologics
• Identifying high growth, high stability operating conditions in bioprocess scale-up
• Comparing separate efficiency across operating conditions in downstream processing
• Embedding and viewing SnapGene files and plasmid constructs in molecular biology
• Tracking viral line development genealogy in cell & gene therapy
• Evaluating binding effectiveness with target cells and proteins in cellular assay development
• Searching qPCR data by engineered plasmid constructs
• Traceability and failure analysis for batteries (powder to part)
• Automatic data ingestion for battery cycling data
• Assigning complex builds and tracking status of individual cells
• Calculating active mass of a cell and normalizing cycling data
• Exploring component effects on battery cell performance
• Designing mixtures with bespoke formulation calculations for biomaterials
• Generating individually barcoded samples for analysis
• Incorporating intermediate sample generation in product workflows
• Comparing formulation composition effects on product outputs
• Integrating complex stoichiometric calculations for construction materials
• Tracking recipes and properties across multi-layer products
• Analyzing and modeling cement properties on concrete performance
• Centralizing quality data and documentation
• Managing quality events, control plans, test results, and documentation
• Quickly retrieving past results, reports, and approvals
• Resolving deviations faster with AI tooling for root cause analysis
• Connecting test results directly to specific formulations, batches, or production runs
• Automating quality workflows (test reviews, CAPA, non-conformance management)
• Assigning tasks and sending alerts for quality processes
• Replacing spreadsheets and manual tracking in quality
• Maintaining detailed audit trails and version histories for quality events
• Generating compliance-ready documentation (ISO, GxP)
• Harmonizing quality practices across multiple labs or plants
• Integrating QC LIMS with R&D and production systems
• Linking quality events to formulations, samples, and experiments
• Tracing non-conformities through CAPA process
• Pulling in results and syncing with ERPs

AI approach

Uncountable leverages proprietary machine learning algorithms and an AI assistant named Bodie to enhance R&D, QC, and PLM processes. Bodie provides conversational search, automated insight generation, summarization, visualization creation, and direct platform actions. The platform uses historical data for predictive formulation modeling, production pattern recognition, and AI-guided optimization, tailored to scientific experimentation.

Tech named: machine learning algorithms, AI assistant, predictive formulation modeling, production pattern recognition, AI-guided optimization, correlation analysis, DOE (Design of Experiments)

Industries served

• Chemicals
• Advanced Materials
• Consumer Goods
• Food and Agriculture
• Pharmaceuticals
• Coatings & Paints
• Cosmetics
• Personal Care
• Bio-Based Chemicals
• Petrochemical
• Catalyst
• Batteries
• Composites
• Plastics & Compounding
• Rubber
• Construction Materials
• Pharma & Biotech
• Small Molecule Drug Development
• Biologics Drug Development
• CAR-T Therapy
• Gene Therapy
• Biomaterials
• Alternative Proteins
• Enzymes
• Plant Engineering
• Crop Protection
• Automotive
• 3D Printing
• Manufacturing
• Fiber Optic Materials and Coatings
• Adhesives and Sealants
• Abrasives
• Alternative Meat Industry

What it says sets it apart

• AI Platform for end-to-end product development
• Unifies fragmented data from legacy point systems into a single data layer
• Proprietary machine learning algorithms tailored for scientific experimentation
• Bodie AI Assistant for conversational search, analysis, and reporting
• DOE Copilot for designed experiments
• Market-leading platform designed by industry experts for industry experts
• Tailored solutions to meet unique industry and organizational needs
• Unified R&D data platform for company-wide visibility
• Secure infrastructure hosted on Amazon Web Services (AWS)
• Independently-verified best practices for storing & securing data
• SOC 2 Certified, ISO 27001, FDA 21 CFR 11, and GMP compliance
• Audit trail of all actions and electronic signature support
• Full lot traceability and shelf life management
• Integration with Microsoft Office for document editing
• Formulation-first data model for centralizing product data
• Full-lifecycle visibility from concept to continuous improvement
• Cross-functional alignment for R&D, quality, manufacturing, and regulatory teams
• Predictive formulation modeling to reduce costly experimentation
• Production pattern recognition for trend detection
• AI-guided optimization for experiment suggestions
• Integrated LIMS and ELN solutions to unify laboratory information
• Configurable and adaptable to unique operational processes
• Connects with 400+ instrument types and network configurations
• Automated workflows and task scheduling to optimize lab efficiency
• Customizable permissions and accessibility for enhanced security
• Seamless bi-directional data flow and frictionless integration
• Built-in project management within the platform
• 20+ visualization tools to replace standalone tooling like Tableau, JMP, MiniTab
• Built-in statistical analysis tools like ANOVA and DOE creation
• Machine learning solutions to suggest next experiments based on organizational data
• Ability to share graphs and reports with other users within the system
• Real-time updates for graphs and data in reports
• Links ingredients, processing conditions, and test results across every build for advanced materials
• Structures discovery, formulation, and process data in one platform for pharma & biotech
• Supports small molecule, biologics, and cell & gene therapy drug development
• Centralizes formulations, sensory and analytical data, and process parameters for food & beverage
• AI tooling for quicker root cause analysis in QC
• Integrated QC LIMS offers flexibility of standalone systems but simplifies insights
• Customer ownership of data and full data exports available
• GDPR compliance
• Third-party penetration tests conducted yearly

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.